Questions tagged [machine-learning]

For questions related to the use of machine learning techniques (neural networks, support vector machines, Gaussian process regression, etc) to study material or molecular properties.

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Is it possible to build a force field that suits all elements based on vasp's machine learning result?

I have tried to use VASP's machine learning force field calculation during running molecular dynamics simulation with a supercell including some elements of Ti, O, Cu, etc. It does increase the speed ...
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6 votes
1 answer
156 views

Getting interpretable chemical information from hashed molecular fingerprints

I have been using molecular fingerprints like ECFP (extended connectivity fingerprint), APFP (atom-pair fingerprint) etc. in my research to predict spectral properties of organic molecules with ...
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5 votes
1 answer
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PyTorch WL Kernel

I’m learning to use PyTorch Geometric, I tried to replicate the WL kernel written by the PyG developers on GitHub (https://github.com/pyg-team/pytorch_geometric/blob/master/examples/wl_kernel.py), but ...
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15 votes
1 answer
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What are the advantages of (semi)-empirical force fields over Machine Learning Potentials?

I am currently working with ReaxFF, an empirical reactive force field that can describe chemical bond forming and breaking. The main advantage over ab initio methods are of course the greatly ...
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6 votes
1 answer
109 views

How to improve my cross-validation R2_score?

I built a prediction model with fingerprints from 300 molecules and got an R2 of 0.9 However when I go to perform a cross-validation I get a very low R2. How can I improve this result? I'm using ...
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14 votes
1 answer
633 views

How to start a Machine Learning project for chemical properties prediction?

I know that is a very general question but I would like to start a ML project in Python to predict some chemical properties with a large set of experimental data. The compounds I would like to study ...
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10 votes
1 answer
112 views

Node features matrix with Networkx

I built a function to generate graphs from smiles strings using networkx, inserting various features on the nodes. This is the code: ...
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9 votes
0 answers
50 views

Graph Classification via Random Forest

I’m a medicinal chemistry undergraduate student who is preparing his dissertation. My idea would be to create a classifier that can distinguish anticancer drugs as active or inactive and distinguish ...
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8 votes
2 answers
742 views

How to input 3D coordinates from xyz file and connectivity from SMILES in rdkit?

I am working on a QSAR project where the 3D structural descriptors are an input to a machine learning model. I am generating the descriptors using the python Mordred API (which uses rdkit). ...
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13 votes
1 answer
110 views

How are structure descriptors used in regression or machine learning?

I am currently working on prediction of UV-vis spectra from structure of molecules. I have read multiple papers where structure descriptors were used as inputs for machine learning to find various ...
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6 votes
1 answer
127 views

FireWorks for Workflow management or TensorFlow

In computational material science, we need workflows for optimization surrogate models which requires high computation resources. I am actually concerned with why material science community is using ...
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9 votes
0 answers
93 views

Is "Valence Electron Density" and "Electron Density" data of a molecule the same thing? [closed]

I'm wondering specifically in the context of calculating physical properties from valence-electron-density data using DFT, MD, and or ML (machine learning).
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10 votes
1 answer
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Is there a database where one can find the Electron Density data of materials?

The database I am looking for may be experimental, computational or user-generated data. If I end up using the data, I will be providing the necessary citations and credits. Thank You.
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12 votes
1 answer
169 views

What are the databases of semiconductor properties?

Is there any database listing the experimentally-determined properties of semiconductor materials - things like Band Gap and Electron Mobility. These are easily found for common materials like ...
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7 votes
0 answers
63 views

Should one normalize the "features" in binary fingerprints? [closed]

In regression models to predict chemical compounds' activities, fingerprints are often used as features. Should one normalize a fingerprint feature to be in the 0-1 range?
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17 votes
1 answer
743 views

Deep Neural Networks: Are they able to provide insights for the many-electron problem or DFT?

The solution of the many-electron Schrodinger equation is the key to understand the properties of matter. However, it is notorious due to the exponential wall (for example, see section II (C) of ...
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18 votes
1 answer
855 views

Does DeepMind's new protein folding software (AlphaFold) also work well for metalloproteins (proteins with metal cofactors)?

(1) Commonly, the metal is at the active site which needs the most prediction precision. (2) Typically, there is only one (or a few) metals in a protein, which contains far more other atoms. So, the ...
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53 votes
3 answers
9k views

DeepMind just announced a breakthrough in protein folding, what are the consequences?

There was some recent media reporting about a purported Google breakthrough on applying machine learning techniques to tackle the protein folding problem, as told for example in this news article, ...
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3 votes
1 answer
59 views

How to proceed with learning application of Machine Learning in material modelling?

This might be very broad question. Since ML application in Matter Modelling is emerging field it would good to understand how it is applied and why it is useful.
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11 votes
2 answers
115 views

What are some available software packages for automated finding of local and absolute minima on PES?

I have never used any AI driven calculation package before and to be honest don't fully understand the ins and outs of it. To be more specific I'm looking for something that can find local minima for ...
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15 votes
1 answer
96 views

Which modelling package currently implements an AI derived force field?

I would like to use an AI-derived force field as they seemed to have lesser computational cost. Which simulation package (Gromacs, Amber, NAMD...) currently implement some of them?
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25 votes
1 answer
178 views

Benchmark Timings of Machine Learning Potentials vs Molecular Mechanics Force Fields

Machine learning is an increasingly common tool for developing force fields for molecular dynamics simulations. It's not totally clear what should be considered a machine-learning potential, but let's ...
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16 votes
2 answers
199 views

General Techniques for Smart Sampling in Matter Machine Learning?

This question is somewhat broad, but hopefully I can convey my point and elicit some worthwhile discussion. One of the fundamental difficulties of machine learning is trying to develop a model that ...
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9 votes
2 answers
415 views

Can Machine Learning lead to the more accurate theories and methods for matter modeling?

There's no doubt about it. Machine Learning (ML) is one of the hottest topics out there and it plays an important role in computational science. One application I have seen is to use ML and Density ...
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33 votes
2 answers
498 views

Machine learning interatomic potentials for molecular dynamic simulations: are they good?

I know the general question of machine learning in computational chemistry has been already raised here: What is the current status of machine learning applied to materials or molecular systems? ...
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23 votes
1 answer
199 views

What are some examples of active learning methods used in atomistic machine learning?

Many machine learning attempts in atomistic applications (see this answer) seem to parameterize models on calculated data (i.e., CCSD(T), DFT, etc.). This approach suggests some automatic procedure ...
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18 votes
1 answer
214 views

What is the state of the art in terms of local atomic environment descriptors for machine learning?

A lot of atomistic machine learning deals with correctly describing atomic neighborhood environments by vectors or fingerprints (see, e.g. J. Chem. Phys. 149, 244102 (2018), Phys. Rev. B 87, 184115 (...
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28 votes
2 answers
409 views

What is the current status of machine learning applied to materials or molecular systems?

I heard that machine learning techniques on materials use a large quantity of data to make predictions of a variety of features; for instance, a crystal structure. Data collected from empirical or ...
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